Soap api testing in python


  • Top API Testing Tools for 2020
  • Smarter Tech Decisions Using APIs
  • Post navigation
  • API Testing Approaches and Tools: Postman, Rest Assured, jMeter, and more
  • Making SOAP API calls using Python
  • 20 Best API Testing Tools in 2021: REST & SOAP Web Services
  • Top API Testing Tools for 2020

    As APIs are becoming the essential component of software development, it is necessary for developers and programmers to perform API tests. Pros: It is free to use. You can test as many APIs on the marketplace as you want. One workspace for 10, public APIs. Rest-assured is an open-source platform with a Java Domain-specific language. Cons: It supports only the Java language. Postman offers a web version as well as a desktop app, and can also be used for testing API services.

    It enables the user to easily share the knowledge with the team. Pros: This tool is easy to use compared to others.

    Easy to set-up parameters on method calls. Ability to store commands. It offers API development capabilities as well. Cons: Pricing for enterprise is high. Enterprise version is easy to set up and use, but the number of requests is limited. Pros: It is easy to use. It has an excellent interface. It is more stable in performance as compared to other API testing tools. It also has multi-dimensional environment settings.

    Cons: Currently, Pas is available for Mac users only. High pricing one-time purchase. SoapUI Pro gives development and testing teams a powerful solution to create, run, and analyze complex tests on web services. Pros: It can create custom codes using Groovy. You can transfer data from one response to multiple API calls without manual intervention.

    It stores your work so that you can revisit it at a later time. This tool lacks documentation. It provides easy development by including all frameworks and plugins in one package. It is suitable for both beginners and experts with the Manual and Scripting modes.

    It can be used for automated and exploratory testing. It is a complete package and framework. Cons: It is difficult to troubleshoot issues. It is hard to debug code, and there are no compile-time error checks. It does not have support for distributed testing. JMeter Apache Jmeter is another open-source software for load and performance testing of applications. It is widely used for functional API testing. It comes with many API testing functionalities and a bunch of features to make the process more efficient.

    Pros: JMeter can be utilized in static and dynamic resource performance testing. It allows developers to replay test results. The interface of JMeter is user-friendly and can be used in a command-line interface. JMeter supports per-thread cookies. It requires skilled testers. Memory consumption is high in GUI mode, which causes it to give out errors for many users. It combines API test-automation, mocks, and performance-testing into a single, unified framework.

    It allows testers to create meaningful tests for web services using a domain-specific language. Pros: Karate DSL supports multi-thread parallel execution. It allows configuration switching.

    Code support becomes very time consuming and expensive. If you are looking for a continuous testing platform for Agile and DevOps, you may consider this one. Pros: Tosca reduces the time of regression testing. The excellent results and dashboards give a nice view into results. The API tests can be used across mobile, cross-browser, packaged apps, etc. It maximizes reuse and maintainability with model-based test automation. Cons: Assertible Assertible is another open-source tool with GitHub forks.

    It mainly focuses on automation and reliability. The sync feature in Assertible allows testers to update their tests when their specifications change.

    In the recent update, Assertible got a new feature called Encrypted variables. Pros: It provides an easy way to create robust tests. It will help you to reduce bugs in your application by allowing you to develop an automated QA system. Cons: The platform might not be convenient if you like viewing a detailed quality report of your web services. Apigee Apigee is another useful tool for API testing.

    Apigee is purpose-built for digital business, and the data-rich mobile-driven APIs and apps that power it.

    Pros: It identifies performance issues by tracking API traffic, error rates, and response times. It supports Node. It is multi-step and powered by JavaScript. Only one user can be active in a proxy at a time.

    It allows you to develop. Net APIs and testing them with the same tool. Supports both asynchronous and synchronous requests.

    Smarter Tech Decisions Using APIs

    Some QAs, however, still ignore this layer of the test pyramid, and proceed right to UI testing — at their peril. In this article, we explain why you should do API testing and how to approach it. We have already written in-depth on what an API is. This time we connect the dots under the topic of API testing.

    What is API testing? API in terms of the three-tier architecture Client, server, and database are the three independent tiers of software architecture. Usually, a client is a web browser or a mobile application that presents the requested info, while business logic is realized on the server side.

    Client and server communicate through requests based on different transfer protocols. The system and logic of protocol-dependent requests are the API itself. The server retrieves the requested data from the database, transforms it according to the business logic, and returns it to the client in a response format, e. Finally, the UI displays it to the user. Why API testing is important A basic concept in automated testing is a test pyramid.

    Following the pattern of the testing pyramid, first is the unit test layer — code testing often performed by developers while writing it. Then comes the server layer where API testing belongs. Later, when the front end is finished, UI testing takes place. Three layers of the test automation pyramid As we already mentioned, API testing is often overlooked.

    But why is it so important? This could leave you with bugs rooted in the server or even at the unit level. But now, the cost of mistakes is way higher as it may require rewriting a considerable amount of code and derail the release. The solution here is to start testing at the early stages. In the Agile processes, where instant feedback is needed, unit and API testing are preferred over GUI testing as they are quicker to create and easier to maintain.

    While the latter requires considerable rework to keep pace with frequent change. So, we encourage you to pay attention to API testing as well and apply it to smooth the overall development workflow. They test whether it returns correct outputs in the expected format, whether it delivers responses within an acceptable timeframe, and how well it integrates with presentation layer software. Functional API tests Functional testing is the assessment of specific functions within the codebase.

    It makes sure the API actually works within expected parameters, meaning it: returns the desired output for a given input; handles errors when the results are outside of the expected parameters. Negative testing checks how an API responds to every possible kind of wrong input, while positive testing verifies the correct functioning of the API when the input conforms to the norm.

    Load testing. The point of load testing is to measure where the limit of system performance under high load lies. Soak testing. Load tests that run over a long period of time can reveal system instabilities like API memory leaks.

    So when you have a weekend ahead, leave automated soak tests running. On Monday, it will show you whether any unwanted behavior has emerged. Stress testing. The idea is to gradually increase the count of virtual users to find the point at which the API starts throwing errors, slows down, or stops responding. Spike testing. Contrary to stress testing, here an API undergoes a sudden spike of users.

    Spike testing checks whether the API is able to stabilize and return to normal functioning after that. Scalability testing. You want to be sure that your system performance scales according to the changing load. To do so, increase the number of incoming requests and monitor whether it causes a proportional increase in response time. Peak testing. Similar to soak testing, here you subject your API to the heaviest load while reducing the time of the attack.

    API security tests Security, penetration, and fuzz testing are the components of the security auditing process aimed at testing an API for vulnerabilities from external threats. Security testing. It validates whether security requirements are met. This includes authentication, permissions, and access controls, namely: What type of authentication is required to use the API; How well sensitive data is encrypted; What authorization checks are set for resource access, etc.

    Penetration testing. Taking security testing a step further, in penetration testing, certain API functions, resources, processes, or the entire API is under attack from the outside. This determines whether the threat vector can be reached. Fuzz testing. The last step in the security audit tests the API at its absolute limits. Forcibly inputting massive amounts of random data, it tests whether the API will stand it or end up with negative behavior like a forced crash or overflow.

    Integration and reliability tests of APIs Being at the center of integrations between internal or third-party services, APIs need to pass the following tests.

    Integration testing. When synced with various devices, an API should be tested for any possible disconnections. When automated, API testing can be easily performed on a regular basis. Its main advantage is speed — less lag time between development and QA, less time spent on debugging in production. We will discuss the most popular solutions in the next section. To be able to plan API tests, first, you need to determine testing boundaries and requirements.

    Step 2: Establish the API test environment. When you determined the functional scope of your API, the next step is setting up an API test environment which is usually the task of DevOps engineers.

    It requires the configuration of the servers, databases, and every resource the API interacts with, depending on the software requirements. Step 3: Make a trial API call. Before diving into thorough testing, make an API call just to check that nothing is broken and the API is operational.

    Step 4: Define the input parameters. Plan all possible input combinations. Step 5: Create API test cases. After all the preparations are done, you can write and execute test cases, and, in the end, compare actual results with the expected ones.

    A good practice is to group them by test category. Examples of API test cases include: testing value in response to the input condition: You define the input and authenticate the output, which can be any type of data or status e. Pass or Fail ; checking the behavior of the API in the system when there is no return value in response; tracking events or interruptions triggered by the output; authenticating the effect on the system after data structure updates; validating resources modified by the API call.

    But, it requires specific tools, dedicated to automating it. Using an API testing tool, QAs usually either take advantage of its out-of-the-box solutions or develop a customized framework from its components. Verifying the status code to be via Postman Postman advantages.

    The tool supports many integrations. It has a friendly UI for constructing requests and reading responses, which allows for creating automated tests quite fast.

    Postman runs on local machines, so you can stay in control of your data. Using its command-line tool Newman, you can integrate these tests in continuous integration CI environments. Postman pricing plans. Postman has a free version for small projects. Testing the response time to be less than the timeout via Requests Requests advantages.

    The Requests library saves time and effort by fully automating keep-alive and HTTP connection pooling. Igor Pavlenko considers Requests a powerful library with easy-to-understand documentation , simple syntax, and rich functionality.

    So, the choice is simple — if you have Python — Requests is the best decision for you. Its documentation is stored inside the Github repository. Rest Assured functionality is limited.

    The tool is open-source — another big pro. These days, Apache jMeter also supports functional, regression, and stress tests on different protocols. Its plugins add extensibility and customization, while built-in functions enable dynamic inputs to a test. Thanks to its efficient UI design and lightweight component support, jMeter executes tests fast and provides accurate timing. It caches test results and data providing their offline replay and analysis. It can handle synchronous and asynchronous requests with a wide list of ready-made authenticators.

    Uploading files and forms in multiple parts, RestSharp cuts down on upload times. They also have LoadUI for performance testing. We have already described another SmartBear product used for UI testing — TestComplete — in our article on automated testing tools. SoapUI advantages. It has broad language support Python, JavaScript,etc. The tool comes with out-of-the-box plugins for popular CI servers.

    The solution here is to start testing at the early stages. In the Agile processes, where instant feedback is needed, unit and API testing are preferred over GUI testing as they are quicker to create and easier to maintain. While the latter requires considerable rework to keep pace with frequent change. So, we encourage you to pay attention to API testing as well and apply it to smooth the overall development workflow.

    They test whether it returns correct outputs in the expected format, whether it delivers responses within an acceptable timeframe, and how well it integrates with presentation layer software.

    Functional API tests Functional testing is the assessment of specific functions within the codebase. It makes sure the API actually works within expected parameters, meaning it: returns the desired output for a given input; handles errors when the results are outside of the expected parameters. Negative testing checks how an API responds to every possible kind of wrong input, while positive testing verifies the correct functioning of the API when the input conforms to the norm.

    Load testing. The point of load testing is to measure where the limit of system performance under high load lies. Soak testing. Load tests that run over a long period of time can reveal system instabilities like API memory leaks. So when you have a weekend ahead, leave automated soak tests running.

    On Monday, it will show you whether any unwanted behavior has emerged. Stress testing. The idea is to gradually increase the count of virtual users to find the point at which the API starts throwing errors, slows down, or stops responding. Spike testing. Contrary to stress testing, here an API undergoes a sudden spike of users. Spike testing checks whether the API is able to stabilize and return to normal functioning after that. Scalability testing. You want to be sure that your system performance scales according to the changing load.

    To do so, increase the number of incoming requests and monitor whether it causes a proportional increase in response time. Peak testing. Similar to soak testing, here you subject your API to the heaviest load while reducing the time of the attack.

    Post navigation

    API security tests Security, penetration, and fuzz testing are the components of the security auditing process aimed at testing an API for vulnerabilities from external threats. Security testing. It validates whether security requirements are met.

    This includes authentication, permissions, and access controls, namely: What type of authentication is required to use the API; How well sensitive data is encrypted; What authorization checks are set for resource access, etc. Penetration testing. Taking security testing a step further, in penetration testing, certain API functions, resources, processes, or the entire API is under attack from the outside. This determines whether the threat vector can be reached.

    Fuzz testing. The last step in the security audit tests the API at its absolute limits. Forcibly inputting massive amounts of random data, it tests whether the API will stand it or end up with negative behavior like a forced crash or overflow.

    API Testing Approaches and Tools: Postman, Rest Assured, jMeter, and more

    Integration and reliability tests of APIs Being at the center of integrations between internal or third-party services, APIs need to pass the following tests. Integration testing. When synced with various devices, an API should be tested for any possible disconnections. So let's get to it. Although there are a lot of great paid options here are the top free API testing tools you should check out.

    Making SOAP API calls using Python

    Postman Postman is a rest client that started off as a Chrome browser plugin but recently came out with native versions for both Mac and Windows. At a high level, you can use it to send a post request to your web server and it gives you the response back. It allows you to set up all the headers and cookies your API expects, and then check the response when it comes back. Karate DSL Karate allows you to create a test that can sequence calls to any kind of web-service and assert that the responses are as expected.

    Build on top of Cucumber-JVM Can run a test and generate reports like any standard Java project A test can be written without any Java knowledge required Tests are easy to write even for non-programmers Check out a quick example of how to get started using Karate with BDD. It comes in two flavors: Free open source version and Pro Version. Since the free version is open-source, you can actually gain access to the full source code and modify as needed.

    HttpMaster Express HttpMaster describes itself as a web development and test tool to automate testing of websites and services. HttpMaster also allows you to and monitor API responses.

    HttpsMaster project offers global options to customize your API request Parameter capabilities enable you to include dynamic data with your request You can use request chaining to leverage request items to include some data from the previous request with the next request Rest- Assured Rest-Assured is an open-source Java Domain-specific language DSL that makes testing REST service simple. Built off of data-driven testing methods better test coverage and reliability. Provide insightful test report dashboards of all testing stages for better monitor and collaboration across teams.

    Parasoft SOAtest automates the continuous testing of complex systems by creating codeless API test scenarios from manual recordings.

    20 Best API Testing Tools in 2021: REST & SOAP Web Services

    SOAtest efficiently transforms your test artifacts into security and performance tests, increasing reusability and reducing redundancy. Features: Automatically generate codeless API tests that are robust, reusable, and easily shareable.

    Leverage artificial intelligence to create powerful test scenarios in less time than other tools. Keep test assets in sync with evolving systems via automation.


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